Abstract
Inflammatory bowel disease (IBD) incidence has been increasing steadily, most dramatically in the Western developed countries. Treatment often includes lifelong immunosuppressive therapy and surgery. There is a critical need to reduce the burden of IBD and to discover medical therapies with better efficacy and fewer potential side-effects. Repurposing of treatments originally studied in other diseases with similar pathogenesis is less costly and time intensive than de novo drug discovery. This study used a treatment repurposing methodology, the literature-related discovery and innovation (LRDI) text mining system, to identify potential treatments (developed for non-IBD diseases) with sufficient promise for extrapolation to treatment of IBD. By searching for desirable patterns of twenty key biomarkers relevant to IBD (e.g., inflammation, reactive oxygen species, autophagy, barrier function), the LRDI-based query retrieved approximately 9500 records from Medline. The most recent 350 records were further analyzed for proof-of-concept. Approximately 18% (64/350) met the criteria for discovery (not previously studied in IBD human or animal models) and relevance for application to IBD treatment. Many of the treatments were compounds derived from herbal remedies, and the majority of treatments were being studied in cancer, diabetes, and central nervous system disease, such as depression and dementia. As further validation of the search strategy, the query identified ten treatments that have just recently begun testing in IBD models in the last three years. Literature-related discovery and innovation text mining contains a unique search strategy with tremendous potential to identify treatments for repurposing. A more comprehensive query with additional key biomarkers would have retrieved many thousands more records, further increasing the yield of IBD treatment repurposing discovery.